記述言語：英語   掲載種別：研究論文（学術雑誌）  

BACKGROUND: Molecular profiling of non-small cell lung cancer (NSCLC) is crucial for personalized treatment, but obtaining adequate tumor tissue can be challenging. This study evaluated the utility of droplet digital polymerase chain reaction (ddPCR) analysis of bronchial washings (BWs) and serum for detecting driver oncogene mutations in NSCLC patients, comparing its performance to standard tissue genotyping methods. METHODS: In this prospective, multicenter study conducted at two university hospitals in Yokohama, Japan, 73 treatment-naïve NSCLC patients underwent bronchoscopy with BW collection and blood sampling between October 2022 and April 2024. ddPCR was performed on BW and serum samples to detect epidermal growth factor receptor (EGFR; L858R, exon 19 deletions, G719X), KRAS (G12/13), and BRAF (V600E) mutations. Results were compared with standard tissue genotyping methods, including AmoyDx and Oncomine Dx Target Test (DxTT) assays. Turnaround time (TAT) for results was also assessed. The study protocol was approved by the institutional review boards, and all participants provided informed consent. RESULTS: ddPCR analysis of BW samples showed high concordance with tissue genotyping, detecting EGFR mutations in 31.5% of cases (identical to tissue). For common EGFR mutations (L858R and exon 19 deletions), BW genotyping demonstrated 100% sensitivity and 98.0% specificity compared to tissue. TAT was significantly shorter for BW ddPCR compared to tissue genotyping (4.4±1.8 vs. 20.4±7.7 days, P<0.001). Serum ddPCR showed lower sensitivity (7.8% vs. 33.3% for EGFR mutations) compared to tissue genotyping, with detection associated with the presence of bone metastases. KRAS and BRAF mutations were detected at similar rates in BW and tissue samples, but at lower rates in serum. CONCLUSIONS: ddPCR analysis of BWs demonstrates high accuracy and rapid TAT for detecting common driver mutations in NSCLC. This approach represents a promising alternative to tissue biopsy for molecular profiling, potentially expediting treatment decisions. While serum ddPCR showed limited utility, it may complement tissue genotyping in specific clinical scenarios.

DOI： 10.21037/tlcr-24-772

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記述言語：英語   掲載種別：研究論文（学術雑誌）  

The clinical spectrum of COVID-19 includes a wide range of manifestations, from mild symptoms to severe pneumonia. HLA system plays a pivotal role in immune responses to infectious diseases. The purpose of our study was to investigate the association between HLA and COVID-19 severity in a Japanese population. The study included 209 Japanese COVID-19 patients aged ≥20 years. Saliva samples were collected and used to determine the HLA genotype by HLA imputation through genome-wide association analyses. The association between HLA genotype and COVID-19 severity was then evaluated. The allele frequency was compared between patients with respiratory failure (severe group: 91 cases) and those without respiratory failure (non-severe group: 118 cases), categorising the data into three time periods: pre-Omicron epidemic period, Omicron epidemic period, and total period of this study (from January 2021 to May 2023). In comparing the severe and non-severe groups, the frequencies of the HLA-DQA1*01:03 (35.1% vs. 10.5%, odds ratio [OR] = 4.57, corrected p [pc] = 0.041) and -DQB1*06:01 (32.4% vs. 7.9%, OR = 5.54, pc = 0.030) alleles were significantly higher in the severe group during the pre-Omicron epidemic period. During the Omicron epidemic period, HLA-DQB1*06 (32.4% vs. 7.9%, OR = 5.54, pc = 0.030) was significantly higher in the severe group. During total period of this study, HLA-DQA1*01:03 (30.2% vs. 14.4%, OR = 2.57, corrected pc = 0.0013) and -DQB1*06:01 (44.5% vs. 26.7%, OR = 2.20, pc = 0.013) alleles were significantly higher in the severe group. HLA-DQB1*06:01 and -DQA1*01:03 were in strong linkage disequilibrium with each other (r2 = 0.91) during total period of this study, indicating that these two alleles form a haplotype. The frequency of the HLA-DQA1*01:03-DQB1*06:01 in the severe group was significantly higher than in the non-severe group during pre-Omicron epidemic period (32.4% vs. 7.9%, OR = 5.59, pc = 0.00072), and total period of this study (28.6% vs. 13.1%, OR = 2.63, pc = 0.0013). During Omicron epidemic period, the haplotype did not demonstrate statistical significance, although the odds ratio indicated a value greater 1. Frequencies of the HLA-DQA1*01:03 and -DQB1*06:01 alleles were significantly higher in severe COVID-19 patients, suggesting that these alleles are risk factors for severe COVID-19 pneumonia in the Japanese population.

DOI： 10.1111/tan.15609

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記述言語：英語   掲載種別：研究論文（学術雑誌）  

BACKGROUND: For simultaneous prediction of phenotypic drug susceptibility test (pDST) for multiple antituberculosis drugs, the whole genome sequencing (WGS) data can be analyzed using either a catalog-based approach, wherein 1 causative mutation suggests resistance, (eg, World Health Organization catalog) or noncatalog-based approach using complicated algorithm (eg, TB-profiler, machine learning). The aim was to estimate the predictive ability of WGS-based tests with pDST as the reference, and to compare the 2 approaches. METHODS: Following a systematic literature search, the diagnostic test accuracies for 14 drugs were pooled using a random-effect bivariate model. RESULTS: Of 779 articles, 44 with 16 821 specimens for meta-analysis and 13 not for meta-analysis were included. The areas under summary receiver operating characteristic curve suggested test accuracy was excellent (0.97-1.00) for 2 drugs (isoniazid 0.975, rifampicin 0.975), very good (0.93-0.97) for 8 drugs (pyrazinamide 0.946, streptomycin 0.952, amikacin 0.968, kanamycin 0.963, capreomycin 0.965, para-aminosalicylic acid 0.959, levofloxacin 0.960, ofloxacin 0.958), and good (0.75-0.93) for 4 drugs (ethambutol 0.926, moxifloxacin 0.896, ethionamide 0.878, prothionamide 0.908). The noncatalog-based and catalog-based approaches had similar ability for all drugs. CONCLUSIONS: WGS accurately identifies isoniazid and rifampicin resistance. For most drugs, positive WGS results reliably predict pDST positive. The 2 approaches had similar ability. CLINICAL TRIALS REGISTRATION: UMIN-ID UMIN000049276.

DOI： 10.1093/infdis/jiad480

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記述言語：英語   掲載種別：研究論文（学術雑誌）  

BACKGROUND: Combining multiple tumor markers increases sensitivity for lung cancer diagnosis in the cost of false positive. However, some would like to check as many as tumor markers in the fear of missing cancer. We though to propose a panel of fewer tumor markers for lung cancer diagnosis. METHODS: Patients with suspected lung cancer who simultaneously underwent all six tests [carcinoembryonic antigen (CEA), cytokeratin-19 fragment (CYFRA), squamous cell carcinoma-associated antigen (SCC), neuron-specific enolase (NSE), pro-gastrin-releasing peptide (ProGRP), and sialyl Lewis-X antigen (SLX)] were included. Tumor markers with significant impact on the lung cancer in a logistic regression model were included in our panel. Area under the curve (AUC) was compared between our panel and the panel of all six. RESULTS: We included 1,733 [median 72 years, 1,128 men, 605 women, 779 (45%) confirmed lung cancer]. Logistic regression analysis suggested CEA, CYFRA, and NSE were independently associated with the lung cancer diagnosis. The panel of these three tumor markers [AUC =0.656, 95% confidence interval (CI): 0.630-0.682, sensitivity 0.650, specificity 0.662] had better (P<0.001) diagnostic performance than six tumor markers (AUC =0.575, 95% CI: 0.548-0.602, sensitivity 0.829, specificity 0.321). CONCLUSIONS: Compared to applying all six markers (at least one marker above the upper limit of normal), the panel with three markers (at least one marker above the upper limit of normal) led to a better predictive value by lowering the risk of false positives.

DOI： 10.21037/tlcr-23-855

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記述言語：英語   掲載種別：研究論文（学術雑誌）  

BACKGROUND: The ILD-GAP scoring system is known to be useful in predicting prognosis in patients with interstitial lung disease (ILD). An elevated monocyte count was associated with increased risks of IPF poor prognosis. We examined whether the ILD-GAP scoring system combined with the monocyte ratio (ILD-GAPM) is superior to the conventional ILD-GAP model in predicting ILD prognosis. METHODS: In patients with ILD treated between April 2013 and April 2017, we were retrospectively assessed the relationships between baseline clinical parameters, including age, sex, Charlson Comorbidity Index score (CCIS), ILD diagnosis, blood biomarkers, pulmonary function test results, and disease outcomes. In ILD patients were included idiopathic pulmonary fibrosis (IPF), idiopathic nonspecific interstitial pneumonia (iNSIP), collagen vascular disease-related interstitial pneumonia (CVD-IP), chronic hypersensitivity pneumonitis (CHP), and unclassifiable ILD (UC-ILD). We also assessed the ability to predict prognosis was compared between the ILD-GAP and ILD-GAPM models. RESULTS: A total of 179 patients (mean age, 73 years) were assessed. All of them were taken pulmonary function test, including percentage predicted diffusion capacity for carbon monoxide. ILD patients included 56 IPF cases, 112 iNSIP and CVD-IP cases, 6 CHP cases and 5 UC-ILD cases. ILD-GAPM provided a greater area under the receiver-operating characteristic curve (0.747) than ILD-GAP (0.710) for predicting 3-year ILD-related events. Furthermore, the log-rank test showed that the Kaplan-Meier curves in ILD-GAPM were significantly different by stage (P = 0.015), but not by stage in ILD-GAP (P = 0.074). CONCLUSIONS: The ILD-GAPM model may be a more accurate predictor of prognosis for ILD patients than the ILD-GAP model.

DOI： 10.1186/s12890-023-02833-6

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